PYB1:Introducing
Psychology:
Research Methods
Revision Material
PYB1 Research Methods
Planning Research
(1) Aims & Hypotheses.
(2) Variables.
(3) Populations, samples &
sampling techniques.
(4) Pilot studies
PYB1 Research Methods
Aims & Hypotheses
The Aim of the study tells
us why it is being carried
out (= more general than
the hypothesis).
The Hypothesis tells us
what the study has been
designed to test (= more
specific).
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Formulating Hypotheses
Hypothesis
A precise testable statement, usually proposes a
possible relationship between 2 variables.
Null Hypothesis (H0)
A prediction that the independent variable will have no
effect on the dependent variable, (there will be no
significant difference between the conditions or
results are due to chance).
Alternative/Experimental Hypothesis (H1)
What researcher aims to prove or disprove (the
outcome/ what you are expecting to see). A
prediction that there will be a relationship between
the variables being studied – the independent
variable will have an effect on the dependent
variable.
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Formulating Hypotheses (2)
Types of Experimental Hypothesis
One tailed/directional hypothesis
Prediction of the direction of effect on independent
variable on dependent variable (e.g. loud noise
will reduce a person’s ability to learn a list of
words). Predicts a change and the direction of
the change.
Two tailed/ non-directional
hypothesis
Predicts that independent variable will have an
effect on dependent variable but doesn’t predict
direction of effect. (e.g. loud noise will have an
effect on a person’s ability to learn a list of
words) Predicts a change but not the direction
of the change.
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Variables
(Anything which can change or be changed)
Independent Variable (IV)
= what the researcher manipulates to
see if there is a change in another
variable.
Dependent Variable (DV)
= what is being measured/assessed.
The variable that is affected by the
independent variable
Extraneous/Confounding Variable
(EV)
= variables which might get in the way
of the link between IV & DV so they
must be controlled.
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Selection of participants
Target Population
The whole group of people being studied, from which the sample is taken.
Sample
The actual participants studied. The larger the sample, the more likely it is
to be representative of the target population.
Representative Sample
Participants who are representative/ typical of the target population, all
characteristics of the target population are represented (e.g. gender,
age). If the sample group is representative then the results can be
applied to the whole population.
Sampling Bias
When the sample is non-representative – some characteristics of the
population are under or over-represented, sample doesn’t accurately
represent population.
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Sampling Methods
Opportunity Stratified Sampling
Sampling Sample= made up of sub-
Sample = who is groups representing each
available & willing strata of target population
Systematic Sampling
Random Sampling Sample = members of target
Sample = every member population chosen by a
of target population system e.g. every 5th
has equal chance of person on list
being chosen
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Opportunity Sampling Random Sampling Stratified Sampling Systematic Sampling
Definition Frequently used, Every member of the Variables considered to be Members of target
sample based on who target population has relevant to the study are population are picked
is available at the time an equal chance of identified and sample is on the basis of a
of the study and is being included in the divided into subgroups (strata) system, e.g. every 10th
willing to take part sample. E.G. taking representing those variables. person on the list.
names out of a hat, get Each subgroup must be Easier/ modified
computer to pick represented in the sample in version of random
random numbers same proportion to which it sampling.
appears in target population.
Strengths Straightforward, Avoids experimenter Provides representative Easier than random
easy bias in selecting sample sample (more than other sampling
Widely used & Should be no bias in methods) Faster than random
accepted who is selected sampling
Quick, convenient, Relatively unbiased
economical
Weaknesses might not be may not be Very time consuming/ Not as effective as
representative of representative expensive random sampling
target population may not be possible to Required very detailed
may be sample bias/ contact all members of knowledge of target population
researcher bias target population, some which can be difficult to find
may refuse to take part out
Can be time
consuming & expensive Methods
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Pilot Studies
Pilot study = an first run-
through of the investigation
to check design of study
before conducting in full.
Advantages:
• Save time & money by
identifying flaws
• Any ambiguities/ confusion
in task/ information will come
to light
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Methods of
Investigation
(1) Methods of Investigation
(2) Experimental Design
(3) Observations
(4) Interviews
(5) Questionnaires
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Methods of
Investigation
Experiment
Most often used, controlled, very scientific.
Correlational Studies
Studies examining an association/link between 2 factors
Case Studies
Detailed study of single individual/event/group
Observational Studies
Examining behaviour without manipulating it
Interviews & Questionnaires
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Experimental Design
Independent Groups
= different people used for each
condition in the experiment.
Repeated Measures
= each participant appears in
both/all conditions/groups.
Matched Pairs
= 2 groups of participants are
used (1 for each condition) &
matching process is used to
ensure 2 groups = as similar as
possible.
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Observations
Participant
: observer is part of the group of
individuals being observed
Non-participant
: observer is not part of the
group of individuals being
observed
Covert
: those being observed are
unaware of observation
Overt
: those being observed are
aware of observation
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Interviews
Structured Interviews
= fixed, pre-determined
questions & often a fixed
set of possible responses.
Unstructured Interviews
= may contain topic area for
discussion but no fixed
questions, more informal.
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Questionnaires
Open Questions
- allow respondents to
answer in whatever way
they wish
Closed Questions
- invite respondents to
select from a range of
possible answers
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Representing Data &
Descriptive Statistics
(1) Descriptive statistics - measures of central tendency
(2) Descriptive statistics - measures of dispersion
(3) Descriptive statistics - correlation
(4) Representing data – bar charts
(5) Representing data – histograms
(6) Representing data – scattergrams
(7) Representing data – line graphs
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Measures of central
tendency (Averages)
Mean
= sum of scores divided by
number of scores
Median
= middle score
Mode
= most frequently
occurring score
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Measures of dispersion
The range
= difference between the lowest &
highest value in a set.
The standard deviation
= more accurate measure of
dispersion, examines how
scores cluster around the
mean.
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Correlation
Correlation
Describes the relationship between
two variables.
Positive Correlation
High values on one variable are
associated with high values on
the other.
Negative Correlation
High values on one variable are
associated with low values on
the other.
Zero Correlation
There is no linear relationship
between the 2 variables, either
positive or negative.
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Representing Data:
Bar Charts
Bar Charts
Displays frequencies of discrete
variables.
X-axis = usually categories
Y- axis = usually frequency (how
often something has
occurred)
Must Include:
• Title
• Labelled axes
• Key
• Correct placement of bars
(which should not touch!)
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Representing Data:
Histograms
Histograms
Displays frequencies of continuous
data.
X-axis = continuous variable
(e.g.time)
Y-axis = frequency of occurrence.
Must Include:
• Title
• Labelled axes
• Correct placement of
bars/points (bars should touch!)
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Representing Data:
Scattergrams
Scattergrams
A graphical display of data obtained
using correlation technique.
Data is in pairs: Y-axis = scale
for one of paired values, X-axis
shows scale for the other.
Must Include:
• Title
• Labelled axes
• Correct placement of points
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Representing Data:
Line Graphs
Line Graphs
Used to show the relationship between
independent & dependent variables
Points are joined together to show
connection between scale points on x-
axis
X-axis = IV
Y-axis = DV
Must Include:
• Title
• Labelled axes
• Correct placement of points/line
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Representing Data:
Tables
Tables are the most basic
way of representing
data.
Must Include:
• Title
• Clear labels
• Usual to include
number of participants
used.
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Ethical Issues
Deception
Informed Consent
Confidentiality
Protection from
harm
Debriefing
Right to withdraw
PYB1 Research Methods